Pandas Profiling Report

Dataset statistics

Number of variables	15
Number of observations	660
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	77.5 KiB
Average record size in memory	120.2 B

Variable types

Categorical	5
Numeric	10

Alerts

`Club` has a high cardinality: 180 distinct values	High cardinality
`Player Names` has a high cardinality: 444 distinct values	High cardinality
`Matches_Played` is highly overall correlated with `Mins` and 4 other fields	High correlation
`Mins` is highly overall correlated with `Matches_Played` and 4 other fields	High correlation
`Goals` is highly overall correlated with `Matches_Played` and 4 other fields	High correlation
`xG` is highly overall correlated with `Matches_Played` and 4 other fields	High correlation
`xG Per Avg Match` is highly overall correlated with `Shots Per Avg Match` and 1 other fields	High correlation
`Shots` is highly overall correlated with `Matches_Played` and 4 other fields	High correlation
`OnTarget` is highly overall correlated with `Matches_Played` and 4 other fields	High correlation
`Shots Per Avg Match` is highly overall correlated with `xG Per Avg Match` and 1 other fields	High correlation
`On Target Per Avg Match` is highly overall correlated with `xG Per Avg Match` and 1 other fields	High correlation
`Country` is highly overall correlated with `League`	High correlation
`League` is highly overall correlated with `Country`	High correlation
`Player Names` is uniformly distributed	Uniform
`Substitution` has 169 (25.6%) zeros	Zeros

Reproduction

Analysis started	2023-08-03 01:35:18.412083
Analysis finished	2023-08-03 01:35:56.720883
Duration	38.31 seconds
Software version	pandas-profiling v3.6.6
Download configuration	config.json

Country
Categorical

Distinct	9
Distinct (%)	1.4%
Missing	0
Missing (%)	0.0%
Memory size	5.3 KiB

Spain	100
Italy	100
Germany	100
Brazil	100
England	80
Other values (4)	180

Length

Max length	12
Median length	9
Mean length	6.3333333
Min length	3

Characters and Unicode

Total characters	4180
Distinct characters	29
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Spain
2nd row	Spain
3rd row	Spain
4th row	Spain
5th row	Spain

Common Values

Value	Count	Frequency (%)
Spain	100	15.2%
Italy	100	15.2%
Germany	100	15.2%
Brazil	100	15.2%
England	80	12.1%
France	60	9.1%
USA	40	6.1%
Portugal	40	6.1%
Netherlands	40	6.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
spain	100	15.2%
italy	100	15.2%
germany	100	15.2%
brazil	100	15.2%
england	80	12.1%
france	60	9.1%
usa	40	6.1%
portugal	40	6.1%
netherlands	40	6.1%

Most occurring characters

Value	Count	Frequency (%)
a	620	14.8%
n	460	11.0%
l	360	8.6%
r	340	8.1%
e	240	5.7%
i	200	4.8%
y	200	4.8%
t	180	4.3%
S	140	3.3%
d	120	2.9%
Other values (19)	1320	31.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3360	80.4%
Uppercase Letter	740	17.7%
Space Separator	80	1.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	620	18.5%
n	460	13.7%
l	360	10.7%
r	340	10.1%
e	240	7.1%
i	200	6.0%
y	200	6.0%
t	180	5.4%
d	120	3.6%
g	120	3.6%
Other values (8)	520	15.5%

Uppercase Letter

Value	Count	Frequency (%)
S	140	18.9%
B	100	13.5%
G	100	13.5%
I	100	13.5%
E	80	10.8%
F	60	8.1%
U	40	5.4%
A	40	5.4%
P	40	5.4%
N	40	5.4%

Space Separator

Value	Count	Frequency (%)
	80	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4100	98.1%
Common	80	1.9%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	620	15.1%
n	460	11.2%
l	360	8.8%
r	340	8.3%
e	240	5.9%
i	200	4.9%
y	200	4.9%
t	180	4.4%
S	140	3.4%
d	120	2.9%
Other values (18)	1240	30.2%

Common

Value	Count	Frequency (%)
	80	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4180	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	620	14.8%
n	460	11.0%
l	360	8.6%
r	340	8.1%
e	240	5.7%
i	200	4.8%
y	200	4.8%
t	180	4.3%
S	140	3.3%
d	120	2.9%
Other values (19)	1320	31.6%

League
Categorical

Distinct	28
Distinct (%)	4.2%
Missing	0
Missing (%)	0.0%
Memory size	5.3 KiB

La Liga	100
Serie A	100
Bundesliga	100
Campeonato Brasileiro SÃ©rie A	100
Premier League	80
Other values (23)	180

Length

Max length	30
Median length	15
Mean length	12.777273
Min length	3

Characters and Unicode

Total characters	8433
Distinct characters	38
Distinct categories	5 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	La Liga
2nd row	La Liga
3rd row	La Liga
4th row	La Liga
5th row	La Liga

Common Values

Value	Count	Frequency (%)
La Liga	100	15.2%
Serie A	100	15.2%
Bundesliga	100	15.2%
Campeonato Brasileiro SÃ©rie A	100	15.2%
Premier League	80	12.1%
Primeira Liga	40	6.1%
MLS	40	6.1%
Eredivisie	40	6.1%
France Ligue 12	3	0.5%
France Ligue 9	3	0.5%
Other values (18)	54	8.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
a	200	14.3%
liga	140	10.0%
la	100	7.1%
serie	100	7.1%
bundesliga	100	7.1%
campeonato	100	7.1%
brasileiro	100	7.1%
sã©rie	100	7.1%
premier	80	5.7%
league	80	5.7%
Other values (25)	300	21.4%

Most occurring characters

Value	Count	Frequency (%)
e	1160	13.8%
i	980	11.6%
a	820	9.7%
	740	8.8%
r	740	8.8%
L	420	5.0%
g	380	4.5%
o	300	3.6%
n	260	3.1%
S	240	2.8%
Other values (28)	2393	28.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	5980	70.9%
Uppercase Letter	1520	18.0%
Space Separator	740	8.8%
Other Symbol	100	1.2%
Decimal Number	93	1.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1160	19.4%
i	980	16.4%
a	820	13.7%
r	740	12.4%
g	380	6.4%
o	300	5.0%
n	260	4.3%
s	240	4.0%
u	240	4.0%
m	220	3.7%
Other values (6)	640	10.7%

Uppercase Letter

Value	Count	Frequency (%)
L	420	27.6%
S	240	15.8%
A	200	13.2%
B	200	13.2%
P	120	7.9%
Ã	100	6.6%
C	100	6.6%
F	60	3.9%
M	40	2.6%
E	40	2.6%

Decimal Number

Value	Count	Frequency (%)
1	36	38.7%
2	9	9.7%
9	6	6.5%
0	6	6.5%
7	6	6.5%
8	6	6.5%
5	6	6.5%
3	6	6.5%
4	6	6.5%
6	6	6.5%

Space Separator

Value	Count	Frequency (%)
	740	100.0%

Other Symbol

Value	Count	Frequency (%)
©	100	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7500	88.9%
Common	933	11.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1160	15.5%
i	980	13.1%
a	820	10.9%
r	740	9.9%
L	420	5.6%
g	380	5.1%
o	300	4.0%
n	260	3.5%
S	240	3.2%
s	240	3.2%
Other values (16)	1960	26.1%

Common

Value	Count	Frequency (%)
	740	79.3%
©	100	10.7%
1	36	3.9%
2	9	1.0%
9	6	0.6%
0	6	0.6%
7	6	0.6%
8	6	0.6%
5	6	0.6%
3	6	0.6%
Other values (2)	12	1.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8233	97.6%
None	200	2.4%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1160	14.1%
i	980	11.9%
a	820	10.0%
	740	9.0%
r	740	9.0%
L	420	5.1%
g	380	4.6%
o	300	3.6%
n	260	3.2%
S	240	2.9%
Other values (26)	2193	26.6%

None

Value	Count	Frequency (%)
Ã	100	50.0%
©	100	50.0%

Club
Categorical

Distinct	180
Distinct (%)	27.3%
Missing	0
Missing (%)	0.0%
Memory size	5.3 KiB

None	34
(PSG)	14
(BAR)	13
(NAP)	13
(RMA)	11
Other values (175)	575

Length

Max length	29
Median length	5
Mean length	4.9984848
Min length	3

Characters and Unicode

Total characters	3299
Distinct characters	46
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	64 ?
Unique (%)	9.7%

Sample

1st row	(BET)
2nd row	(BAR)
3rd row	(ATL)
4th row	(CAR)
5th row	(VAL)

Common Values

Value	Count	Frequency (%)
None	34	5.2%
(PSG)	14	2.1%
(BAR)	13	2.0%
(NAP)	13	2.0%
(RMA)	11	1.7%
(SOC)	11	1.7%
(ATA)	11	1.7%
(FLA)	11	1.7%
(TOT)	11	1.7%
(INT)	10	1.5%
Other values (170)	521	78.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
none	34	5.1%
psg	14	2.1%
bar	13	2.0%
nap	13	2.0%
rma	11	1.7%
soc	11	1.7%
ata	11	1.7%
fla	11	1.7%
tot	11	1.7%
liv	10	1.5%
Other values (174)	526	79.1%

Most occurring characters

Value	Count	Frequency (%)
)	616	18.7%
(	616	18.7%
A	238	7.2%
R	138	4.2%
L	130	3.9%
N	126	3.8%
S	122	3.7%
O	120	3.6%
E	118	3.6%
C	107	3.2%
Other values (36)	968	29.3%

Most occurring categories

Value	Count	Frequency (%)
Uppercase Letter	1888	57.2%
Close Punctuation	616	18.7%
Open Punctuation	616	18.7%
Lowercase Letter	173	5.2%
Space Separator	5	0.2%
Other Punctuation	1	< 0.1%

Most frequent character per category

Uppercase Letter

Value	Count	Frequency (%)
A	238	12.6%
R	138	7.3%
L	130	6.9%
N	126	6.7%
S	122	6.5%
O	120	6.4%
E	118	6.2%
C	107	5.7%
M	92	4.9%
T	91	4.8%
Other values (14)	606	32.1%

Lowercase Letter

Value	Count	Frequency (%)
o	44	25.4%
n	43	24.9%
e	34	19.7%
i	9	5.2%
r	8	4.6%
a	8	4.6%
l	4	2.3%
u	3	1.7%
c	3	1.7%
g	3	1.7%
Other values (8)	14	8.1%

Close Punctuation

Value	Count	Frequency (%)
)	616	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	616	100.0%

Space Separator

Value	Count	Frequency (%)
	5	100.0%

Other Punctuation

Value	Count	Frequency (%)
.	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	2061	62.5%
Common	1238	37.5%

Most frequent character per script

Latin

Value	Count	Frequency (%)
A	238	11.5%
R	138	6.7%
L	130	6.3%
N	126	6.1%
S	122	5.9%
O	120	5.8%
E	118	5.7%
C	107	5.2%
M	92	4.5%
T	91	4.4%
Other values (32)	779	37.8%

Common

Value	Count	Frequency (%)
)	616	49.8%
(	616	49.8%
	5	0.4%
.	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3299	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
)	616	18.7%
(	616	18.7%
A	238	7.2%
R	138	4.2%
L	130	3.9%
N	126	3.8%
S	122	3.7%
O	120	3.6%
E	118	3.6%
C	107	3.2%
Other values (36)	968	29.3%

Player Names
Categorical

HIGH CARDINALITY UNIFORM

Distinct	444
Distinct (%)	67.3%
Missing	0
Missing (%)	0.0%
Memory size	5.3 KiB

Andrea Belotti	5
Lionel Messi	5
Luis Suarez	5
Andrej Kramaric	5
Ciro Immobile	5
Other values (439)	635

Length

Max length	25
Median length	21
Mean length	12.762121
Min length	2

Characters and Unicode

Total characters	8423
Distinct characters	58
Distinct categories	7 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	317 ?
Unique (%)	48.0%

Sample

1st row	Juanmi Callejon
2nd row	Antoine Griezmann
3rd row	Luis Suarez
4th row	Ruben Castro
5th row	Kevin Gameiro

Common Values

Value	Count	Frequency (%)
Andrea Belotti	5	0.8%
Lionel Messi	5	0.8%
Luis Suarez	5	0.8%
Andrej Kramaric	5	0.8%
Ciro Immobile	5	0.8%
Cristiano Ronaldo	5	0.8%
Robert Lewandowski	5	0.8%
Timo Werner	5	0.8%
Iago Aspas	5	0.8%
Fabio Quagliarella	5	0.8%
Other values (434)	610	92.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
diego	9	0.7%
bruno	9	0.7%
kevin	8	0.6%
luis	8	0.6%
carlos	8	0.6%
raul	7	0.6%
fabio	7	0.6%
iago	7	0.6%
andrea	7	0.6%
de	7	0.6%
Other values (698)	1173	93.8%

Most occurring characters

Value	Count	Frequency (%)
a	834	9.9%
e	765	9.1%
	679	8.1%
i	625	7.4%
o	587	7.0%
r	577	6.9%
n	545	6.5%
l	373	4.4%
s	308	3.7%
u	262	3.1%
Other values (48)	2868	34.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6443	76.5%
Uppercase Letter	1272	15.1%
Space Separator	679	8.1%
Dash Punctuation	22	0.3%
Other Punctuation	4	< 0.1%
Control	2	< 0.1%
Format	1	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	834	12.9%
e	765	11.9%
i	625	9.7%
o	587	9.1%
r	577	9.0%
n	545	8.5%
l	373	5.8%
s	308	4.8%
u	262	4.1%
d	227	3.5%
Other values (16)	1340	20.8%

Uppercase Letter

Value	Count	Frequency (%)
M	127	10.0%
A	102	8.0%
S	86	6.8%
D	79	6.2%
B	75	5.9%
L	74	5.8%
R	74	5.8%
G	71	5.6%
C	69	5.4%
P	69	5.4%
Other values (16)	446	35.1%

Other Punctuation

Value	Count	Frequency (%)
'	2	50.0%
.	2	50.0%

Space Separator

Value	Count	Frequency (%)
	679	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	22	100.0%

Control

Value	Count	Frequency (%)
	2	100.0%

Format

Value	Count	Frequency (%)
	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	7715	91.6%
Common	708	8.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	834	10.8%
e	765	9.9%
i	625	8.1%
o	587	7.6%
r	577	7.5%
n	545	7.1%
l	373	4.8%
s	308	4.0%
u	262	3.4%
d	227	2.9%
Other values (42)	2612	33.9%

Common

Value	Count	Frequency (%)
	679	95.9%
-	22	3.1%
'	2	0.3%
	2	0.3%
.	2	0.3%
	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	8418	99.9%
None	5	0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	834	9.9%
e	765	9.1%
	679	8.1%
i	625	7.4%
o	587	7.0%
r	577	6.9%
n	545	6.5%
l	373	4.4%
s	308	3.7%
u	262	3.1%
Other values (45)	2863	34.0%

None

Value	Count	Frequency (%)
Ã	2	40.0%
	2	40.0%
	1	20.0%

Matches_Played
Real number (ℝ)

Distinct	37
Distinct (%)	5.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	22.371212

Minimum	2
Maximum	38
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	2
5-th percentile	6
Q1	14
median	24
Q3	31
95-th percentile	36
Maximum	38
Range	36
Interquartile range (IQR)	17

Descriptive statistics

Standard deviation	9.7546575
Coefficient of variation (CV)	0.43603616
Kurtosis	-1.1303255
Mean	22.371212
Median Absolute Deviation (MAD)	7
Skewness	-0.36923941
Sum	14765
Variance	95.153343
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=37)

Value	Count	Frequency (%)
31	32	4.8%
9	32	4.8%
32	30	4.5%
29	30	4.5%
23	30	4.5%
33	29	4.4%
26	28	4.2%
10	26	3.9%
24	26	3.9%
27	25	3.8%
Other values (27)	372	56.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	1	0.2%
3	5	0.8%
4	3	0.5%
5	6	0.9%
6	24	3.6%
7	22	3.3%
8	24	3.6%
9	32	4.8%
10	26	3.9%
11	12	1.8%

Value	Count	Frequency (%)
38	4	0.6%
37	13	2.0%
36	17	2.6%
35	24	3.6%
34	21	3.2%
33	29	4.4%
32	30	4.5%
31	32	4.8%
30	24	3.6%
29	30	4.5%

Substitution
Real number (ℝ)

Distinct	21
Distinct (%)	3.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.2242424

Minimum	0
Maximum	26
Zeros	169
Zeros (%)	25.6%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	2
Q3	5
95-th percentile	11
Maximum	26
Range	26
Interquartile range (IQR)	5

Descriptive statistics

Standard deviation	3.8394984
Coefficient of variation (CV)	1.1908219
Kurtosis	4.8963123
Mean	3.2242424
Median Absolute Deviation (MAD)	2
Skewness	1.9221552
Sum	2128
Variance	14.741748
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=21)

Value	Count	Frequency (%)
0	169	25.6%
1	130	19.7%
2	80	12.1%
3	65	9.8%
5	43	6.5%
4	35	5.3%
6	34	5.2%
7	21	3.2%
8	20	3.0%
10	13	2.0%
Other values (11)	50	7.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0	169	25.6%
1	130	19.7%
2	80	12.1%
3	65	9.8%
4	35	5.3%
5	43	6.5%
6	34	5.2%
7	21	3.2%
8	20	3.0%
9	10	1.5%

Value	Count	Frequency (%)
26	1	0.2%
23	2	0.3%
18	3	0.5%
17	1	0.2%
16	1	0.2%
15	5	0.8%
14	2	0.3%
13	5	0.8%
12	10	1.5%
11	10	1.5%

Mins
Real number (ℝ)

Distinct	583
Distinct (%)	88.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2071.4167

Minimum	264
Maximum	4177
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	264
5-th percentile	574.95
Q1	1363.5
median	2245.5
Q3	2822
95-th percentile	3271.25
Maximum	4177
Range	3913
Interquartile range (IQR)	1458.5

Descriptive statistics

Standard deviation	900.59505
Coefficient of variation (CV)	0.43477252
Kurtosis	-1.0524114
Mean	2071.4167
Median Absolute Deviation (MAD)	659
Skewness	-0.35736066
Sum	1367135
Variance	811071.44
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
3115	3	0.5%
2312	3	0.5%
872	3	0.5%
669	3	0.5%
567	3	0.5%
822	3	0.5%
903	3	0.5%
1786	2	0.3%
2822	2	0.3%
3236	2	0.3%
Other values (573)	633	95.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
264	1	0.2%
280	1	0.2%
293	1	0.2%
337	1	0.2%
356	1	0.2%
387	1	0.2%
396	1	0.2%
397	1	0.2%
451	1	0.2%
452	1	0.2%

Value	Count	Frequency (%)
4177	1	0.2%
3931	1	0.2%
3651	1	0.2%
3641	1	0.2%
3555	1	0.2%
3533	2	0.3%
3511	1	0.2%
3491	1	0.2%
3474	1	0.2%
3448	1	0.2%

Goals
Real number (ℝ)

Distinct	34
Distinct (%)	5.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	11.810606

Minimum	2
Maximum	42
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	2
5-th percentile	4
Q1	8
median	11
Q3	14
95-th percentile	23
Maximum	42
Range	40
Interquartile range (IQR)	6

Descriptive statistics

Standard deviation	6.0753146
Coefficient of variation (CV)	0.51439482
Kurtosis	2.8916838
Mean	11.810606
Median Absolute Deviation (MAD)	3
Skewness	1.2868065
Sum	7795
Variance	36.909447
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=34)

Value	Count	Frequency (%)
11	67	10.2%
12	64	9.7%
10	55	8.3%
9	50	7.6%
4	48	7.3%
13	47	7.1%
14	37	5.6%
8	36	5.5%
15	30	4.5%
16	29	4.4%
Other values (24)	197	29.8%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	9	1.4%
3	14	2.1%
4	48	7.3%
5	28	4.2%
6	20	3.0%
7	25	3.8%
8	36	5.5%
9	50	7.6%
10	55	8.3%
11	67	10.2%

Value	Count	Frequency (%)
42	1	0.2%
37	1	0.2%
36	3	0.5%
34	1	0.2%
33	2	0.3%
31	3	0.5%
30	1	0.2%
29	5	0.8%
28	4	0.6%
26	3	0.5%

xG
Real number (ℝ)

Distinct	558
Distinct (%)	84.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	10.089606

Minimum	0.71
Maximum	32.54
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	0.71
5-th percentile	2.2775
Q1	6.1
median	9.285
Q3	13.2525
95-th percentile	20.5105
Maximum	32.54
Range	31.83
Interquartile range (IQR)	7.1525

Descriptive statistics

Standard deviation	5.7248437
Coefficient of variation (CV)	0.56740012
Kurtosis	1.2658161
Mean	10.089606
Median Absolute Deviation (MAD)	3.45
Skewness	0.95635774
Sum	6659.14
Variance	32.773835
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
11.62	4	0.6%
3.33	4	0.6%
6.19	3	0.5%
6.11	3	0.5%
11.12	3	0.5%
14.51	3	0.5%
8.56	3	0.5%
8.7	3	0.5%
9.39	3	0.5%
11.09	3	0.5%
Other values (548)	628	95.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.71	1	0.2%
0.8	1	0.2%
0.96	1	0.2%
1.03	1	0.2%
1.05	1	0.2%
1.12	1	0.2%
1.13	1	0.2%
1.31	1	0.2%
1.39	1	0.2%
1.43	1	0.2%

Value	Count	Frequency (%)
32.54	1	0.2%
31.17	1	0.2%
31.05	1	0.2%
30.6	1	0.2%
30.52	1	0.2%
29.27	1	0.2%
29	1	0.2%
28.94	1	0.2%
27.32	1	0.2%
26.65	1	0.2%

xG Per Avg Match
Real number (ℝ)

Distinct	92
Distinct (%)	13.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.47616667

Minimum	0.07
Maximum	1.35
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	0.07
5-th percentile	0.24
Q1	0.34
median	0.435
Q3	0.57
95-th percentile	0.8605
Maximum	1.35
Range	1.28
Interquartile range (IQR)	0.23

Descriptive statistics

Standard deviation	0.19283132
Coefficient of variation (CV)	0.40496602
Kurtosis	1.9127398
Mean	0.47616667
Median Absolute Deviation (MAD)	0.105
Skewness	1.1766357
Sum	314.27
Variance	0.037183918
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.33	23	3.5%
0.39	21	3.2%
0.37	21	3.2%
0.4	20	3.0%
0.41	20	3.0%
0.43	19	2.9%
0.34	18	2.7%
0.57	18	2.7%
0.31	16	2.4%
0.45	16	2.4%
Other values (82)	468	70.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.07	1	0.2%
0.09	1	0.2%
0.15	2	0.3%
0.16	5	0.8%
0.17	1	0.2%
0.18	4	0.6%
0.19	2	0.3%
0.2	1	0.2%
0.21	4	0.6%
0.22	4	0.6%

Value	Count	Frequency (%)
1.35	1	0.2%
1.27	1	0.2%
1.19	2	0.3%
1.16	1	0.2%
1.12	1	0.2%
1.1	1	0.2%
1.08	1	0.2%
1.06	4	0.6%
1.05	1	0.2%
1.01	1	0.2%

Shots
Real number (ℝ)

Distinct	144
Distinct (%)	21.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	64.177273

Minimum	5
Maximum	208
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	5
5-th percentile	14
Q1	37.75
median	62
Q3	86
95-th percentile	124.05
Maximum	208
Range	203
Interquartile range (IQR)	48.25

Descriptive statistics

Standard deviation	34.941622
Coefficient of variation (CV)	0.54445476
Kurtosis	0.62646478
Mean	64.177273
Median Absolute Deviation (MAD)	24
Skewness	0.67615024
Sum	42357
Variance	1220.9169
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
65	13	2.0%
21	13	2.0%
18	12	1.8%
55	12	1.8%
52	11	1.7%
81	11	1.7%
87	10	1.5%
56	10	1.5%
80	9	1.4%
54	9	1.4%
Other values (134)	550	83.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
5	2	0.3%
6	2	0.3%
7	2	0.3%
8	1	0.2%
9	2	0.3%
10	3	0.5%
11	3	0.5%
12	5	0.8%
13	7	1.1%
14	7	1.1%

Value	Count	Frequency (%)
208	1	0.2%
197	1	0.2%
179	1	0.2%
178	2	0.3%
177	1	0.2%
170	1	0.2%
167	1	0.2%
162	1	0.2%
159	2	0.3%
152	1	0.2%

OnTarget
Real number (ℝ)

Distinct	79
Distinct (%)	12.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	28.365152

Minimum	2
Maximum	102
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	2
5-th percentile	7
Q1	17
median	26
Q3	37
95-th percentile	58
Maximum	102
Range	100
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	16.363149
Coefficient of variation (CV)	0.57687509
Kurtosis	2.365776
Mean	28.365152
Median Absolute Deviation (MAD)	10
Skewness	1.1562839
Sum	18721
Variance	267.75265
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
25	26	3.9%
24	20	3.0%
23	20	3.0%
33	20	3.0%
19	20	3.0%
30	19	2.9%
8	19	2.9%
28	18	2.7%
17	17	2.6%
37	17	2.6%
Other values (69)	464	70.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
2	3	0.5%
3	4	0.6%
4	3	0.5%
5	12	1.8%
6	6	0.9%
7	17	2.6%
8	19	2.9%
9	14	2.1%
10	10	1.5%
11	15	2.3%

Value	Count	Frequency (%)
102	1	0.2%
99	1	0.2%
98	1	0.2%
95	1	0.2%
91	1	0.2%
87	1	0.2%
86	1	0.2%
81	1	0.2%
79	1	0.2%
78	2	0.3%

Shots Per Avg Match
Real number (ℝ)

Distinct	280
Distinct (%)	42.4%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.9480152

Minimum	0.8
Maximum	7.2
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	0.8
5-th percentile	1.709
Q1	2.335
median	2.845
Q3	3.3825
95-th percentile	4.54
Maximum	7.2
Range	6.4
Interquartile range (IQR)	1.0475

Descriptive statistics

Standard deviation	0.91490648
Coefficient of variation (CV)	0.3103466
Kurtosis	1.9853344
Mean	2.9480152
Median Absolute Deviation (MAD)	0.53
Skewness	0.94730205
Sum	1945.69
Variance	0.83705387
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2.47	8	1.2%
2.86	8	1.2%
2.75	7	1.1%
2.6	7	1.1%
3.05	7	1.1%
2.22	7	1.1%
2.65	6	0.9%
3.02	6	0.9%
2.49	6	0.9%
2.26	6	0.9%
Other values (270)	592	89.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.8	1	0.2%
0.81	1	0.2%
0.82	1	0.2%
0.85	1	0.2%
0.99	1	0.2%
1.03	1	0.2%
1.16	1	0.2%
1.2	2	0.3%
1.24	1	0.2%
1.27	1	0.2%

Value	Count	Frequency (%)
7.2	1	0.2%
7.12	1	0.2%
6.32	1	0.2%
6.22	1	0.2%
5.99	1	0.2%
5.97	1	0.2%
5.89	1	0.2%
5.84	2	0.3%
5.67	1	0.2%
5.59	1	0.2%

On Target Per Avg Match
Real number (ℝ)

Distinct	184
Distinct (%)	27.9%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.3156515

Minimum	0.24
Maximum	3.63
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	5.3 KiB

Quantile statistics

Minimum	0.24
5-th percentile	0.72
Q1	0.98
median	1.25
Q3	1.54
95-th percentile	2.241
Maximum	3.63
Range	3.39
Interquartile range (IQR)	0.56

Descriptive statistics

Standard deviation	0.4742393
Coefficient of variation (CV)	0.36045966
Kurtosis	2.2392119
Mean	1.3156515
Median Absolute Deviation (MAD)	0.28
Skewness	1.1809319
Sum	868.33
Variance	0.22490291
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.25	13	2.0%
0.94	12	1.8%
1.28	12	1.8%
1.21	12	1.8%
0.96	11	1.7%
1.3	10	1.5%
1.29	10	1.5%
1	10	1.5%
1.11	9	1.4%
1.26	9	1.4%
Other values (174)	552	83.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.24	1	0.2%
0.29	1	0.2%
0.4	1	0.2%
0.48	2	0.3%
0.5	1	0.2%
0.52	1	0.2%
0.54	1	0.2%
0.55	2	0.3%
0.56	4	0.6%
0.58	1	0.2%

Value	Count	Frequency (%)
3.63	1	0.2%
3.11	2	0.3%
3.04	1	0.2%
2.94	1	0.2%
2.9	1	0.2%
2.89	2	0.3%
2.85	1	0.2%
2.84	1	0.2%
2.83	1	0.2%
2.77	1	0.2%

Year
Categorical

Distinct	5
Distinct (%)	0.8%
Missing	0
Missing (%)	0.0%
Memory size	5.3 KiB

2019	200
2020	160
2018	120
2016	100
2017	80

Length

Max length	4
Median length	4
Mean length	4
Min length	4

Characters and Unicode

Total characters	2640
Distinct characters	7
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2016
2nd row	2016
3rd row	2016
4th row	2016
5th row	2016

Common Values

Value	Count	Frequency (%)
2019	200	30.3%
2020	160	24.2%
2018	120	18.2%
2016	100	15.2%
2017	80	12.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2019	200	30.3%
2020	160	24.2%
2018	120	18.2%
2016	100	15.2%
2017	80	12.1%

Most occurring characters

Value	Count	Frequency (%)
2	820	31.1%
0	820	31.1%
1	500	18.9%
9	200	7.6%
8	120	4.5%
6	100	3.8%
7	80	3.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	2640	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	820	31.1%
0	820	31.1%
1	500	18.9%
9	200	7.6%
8	120	4.5%
6	100	3.8%
7	80	3.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	2640	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	820	31.1%
0	820	31.1%
1	500	18.9%
9	200	7.6%
8	120	4.5%
6	100	3.8%
7	80	3.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	2640	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	820	31.1%
0	820	31.1%
1	500	18.9%
9	200	7.6%
8	120	4.5%
6	100	3.8%
7	80	3.0%

Auto

Heatmap
Table

	Matches_Played	Substitution	Mins	Goals	xG	xG Per Avg Match	Shots	OnTarget	Shots Per Avg Match	On Target Per Avg Match	Country	League	Year
Matches_Played	1.000	-0.033	0.978	0.734	0.752	-0.114	0.825	0.791	-0.009	-0.080	0.191	0.174	0.326
Substitution	-0.033	1.000	0.031	0.158	0.111	0.003	0.103	0.104	0.007	-0.016	0.000	0.000	0.133
Mins	0.978	0.031	1.000	0.742	0.766	-0.112	0.835	0.796	-0.014	-0.093	0.207	0.183	0.334
Goals	0.734	0.158	0.742	1.000	0.888	0.320	0.826	0.864	0.299	0.306	0.162	0.091	0.308
xG	0.752	0.111	0.766	0.888	1.000	0.463	0.847	0.862	0.318	0.282	0.157	0.121	0.288
xG Per Avg Match	-0.114	0.003	-0.112	0.320	0.463	1.000	0.159	0.219	0.567	0.619	0.041	0.128	0.079
Shots	0.825	0.103	0.835	0.826	0.847	0.159	1.000	0.943	0.463	0.302	0.161	0.087	0.323
OnTarget	0.791	0.104	0.796	0.864	0.862	0.219	0.943	1.000	0.419	0.439	0.146	0.069	0.330
Shots Per Avg Match	-0.009	0.007	-0.014	0.299	0.318	0.567	0.463	0.419	1.000	0.803	0.077	0.135	0.000
On Target Per Avg Match	-0.080	-0.016	-0.093	0.306	0.282	0.619	0.302	0.439	0.803	1.000	0.100	0.137	0.093
Country	0.191	0.000	0.207	0.162	0.157	0.041	0.161	0.146	0.077	0.100	1.000	0.985	0.287
League	0.174	0.000	0.183	0.091	0.121	0.128	0.087	0.069	0.135	0.137	0.985	1.000	0.231
Year	0.326	0.133	0.334	0.308	0.288	0.079	0.323	0.330	0.000	0.093	0.287	0.231	1.000

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows
Last rows

	Country	League	Club	Player Names	Matches_Played	Substitution	Mins	Goals	xG	xG Per Avg Match	Shots	OnTarget	Shots Per Avg Match	On Target Per Avg Match	Year
0	Spain	La Liga	(BET)	Juanmi Callejon	19	16	1849	11	6.62	0.34	48	20	2.47	1.03	2016
1	Spain	La Liga	(BAR)	Antoine Griezmann	36	0	3129	16	11.86	0.36	88	41	2.67	1.24	2016
2	Spain	La Liga	(ATL)	Luis Suarez	34	1	2940	28	23.21	0.75	120	57	3.88	1.84	2016
3	Spain	La Liga	(CAR)	Ruben Castro	32	3	2842	13	14.06	0.47	117	42	3.91	1.40	2016
4	Spain	La Liga	(VAL)	Kevin Gameiro	21	10	1745	13	10.65	0.58	50	23	2.72	1.25	2016
5	Spain	La Liga	(JUV)	Cristiano Ronaldo	29	0	2634	42	24.68	0.89	162	60	5.84	2.16	2016
6	Spain	La Liga	(RMA)	Karim Benzema	23	6	1967	11	13.25	0.64	69	34	3.33	1.64	2016
7	Spain	La Liga	(PSG)	Neymar	30	0	2694	13	13.33	0.47	105	42	3.70	1.48	2016
8	Spain	La Liga	(CEL)	Iago Aspas	25	7	2354	19	13.88	0.56	78	37	3.15	1.49	2016
9	Spain	La Liga	(EIB)	Sergi Enrich	31	7	2904	11	8.25	0.27	64	26	2.09	0.85	2016

	Country	League	Club	Player Names	Matches_Played	Substitution	Mins	Goals	xG	xG Per Avg Match	Shots	OnTarget	Shots Per Avg Match	On Target Per Avg Match	Year
650	Netherlands	Eredivisie	(AJA)	Klaas-Jan Huntelaar	6	12	938	9	6.91	0.70	32	17	3.24	1.72	2020
651	Netherlands	Eredivisie	(WIL)	Vangelis Pavlidis	25	0	2265	11	12.64	0.53	70	31	2.94	1.30	2020
652	Netherlands	Eredivisie	(EMM)	Michael de Leeuw	26	0	2383	9	8.28	0.33	51	23	2.03	0.92	2020
653	Netherlands	Eredivisie	(PSV)	Donyell Malen	14	0	1245	11	8.91	0.68	59	32	4.50	2.44	2020
654	Netherlands	Eredivisie	(RZA)	Haris Vuckic	23	2	2194	11	6.00	0.26	38	17	1.65	0.74	2020
655	Netherlands	Eredivisie	(UTR)	Gyrano Kerk	24	0	2155	10	7.49	0.33	50	18	2.20	0.79	2020
656	Netherlands	Eredivisie	(AJA)	Quincy Promes	18	2	1573	12	9.77	0.59	56	30	3.38	1.81	2020
657	Netherlands	Eredivisie	(PSV)	Denzel Dumfries	25	0	2363	7	5.72	0.23	45	14	1.81	0.56	2020
658	Netherlands	Eredivisie	None	Cyriel Dessers	26	0	2461	15	14.51	0.56	84	43	3.24	1.66	2020
659	Netherlands	Eredivisie	(PSV)	Cody Gakpo	14	11	1557	7	4.43	0.27	38	15	2.32	0.92	2020

Overview

Variables

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Space Separator

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Space Separator

Other Symbol

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

None

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Uppercase Letter

Lowercase Letter

Close Punctuation

Open Punctuation

Space Separator

Other Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Dash Punctuation

Control

Format

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

None

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category